An Approach for Image Retrieval Based on Support Vector Machines

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 208)


Various approach including artificial neural networks have been used to classify a large image database efficiently and shown to be highly successful in this application area. This paper presents a new, scaling and rotation invariant encoding scheme for shapes. Support vector machines (SVMs) are used for the classifications of shapes encoded by the new method. This paper examines the performance of the proposed method by comparing it with that of multilayer perception, one of the artificial neural network (ANNs) techniques, based on real real-world image data. The experiment shows that the results of one-class SVMs outperform those of ANNs.


Image retrieval Support vector machines Artificial neural network 



This research was supported by the Natural Science Foundation of Luoyang Institute of Science and Technology (Grant No. 2008QZ28).


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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  1. 1.Computer Information Engineering DepartmentLuoYang Institute of Science and TechnologyLuoyang, HenanChina
  2. 2.School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhanChina

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